NIPS Proceedingsβ

Wulfram Gerstner

16 Papers

  • Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments (2015)
  • From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models (2011)
  • Variational Learning for Recurrent Spiking Networks (2011)
  • Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models (2010)
  • Code-specific policy gradient rules for spiking neurons (2009)
  • Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning (2008)
  • An online Hebbian learning rule that performs Independent Component Analysis (2007)
  • Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning (2006)
  • Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects (2005)
  • Integrate-and-Fire models with adaptation are good enough (2005)
  • Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model (2004)
  • Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning (2000)
  • Spike-Based Compared to Rate-Based Hebbian Learning (1998)
  • Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway (1995)
  • How to Describe Neuronal Activity: Spikes, Rates, or Assemblies? (1993)
  • Associative Memory in a Network of `Biological' Neurons (1990)